Introduction to the FAIR-BioRS Guidelines
🌟 Overview
The FAIR Biomedical Research Software (FAIR-BioRS) guidelines are a set of minimal and actionable step-by-step instructions for making biomedical research software FAIR (Findable, Accessible, Interoperable, Reusable), i.e., optimizing their reusability.
❓ When to use the FAIR-BioRS guidelines?
The FAIR-BioRS guidelines were developed for software "that was created during the research process or for a research purpose" as per the definition established in "Defining Research Software: a controversial discussion". Such research software can come in many formats such as Python scripts, R code, or Jupyter notebooks, and can be developed for various applications such as AI/ML models, computational models, or data visualization.
If you are developing such software for biomedical research, The FAIR-BioRS guidelines will help you make your software compliant with the FAIR Principles for Research Software (FAIR4S Principles). This will allow you to get proper recognition (e.g., citation) for your software development effort, enhance the impact of your software (e.g., by being reused in other projects), and increase collaboration opportunities. As funding agencies are pushing for all research outcomes to be FAIR, following the FAIR-BioRS guidelines will also allow you to start complying with those requirements.
💡 Why were these guidelines needed?
Research software is becoming increasingly vital in biomedical research. It plays a fundamental role not only in collecting, analyzing, and processing data but has also become the centerpiece of many research projects aimed at developing computational models to understand and predict various physical phenomena. It is therefore critical to make biomedical research software reusable to ensure the reproducibility of new findings, prevent duplicate efforts, and ultimately increase the pace of discoveries for improving human health.
The Findable, Accessible, Interoperable, and Reusable (FAIR) Guiding Principles published in 2016 constitute the foundation for data management practices adopted by researchers, government agencies, private funders, and scholarly publishers to ensure optimal reusability of data by humans and machines. While postulated for all digital research objects, many in the research software community expressed how they fail to capture the specific traits of software such as dependencies and versioning. Consequently, reformulated FAIR Principles tailored for software have been proposed by different groups. Work from the Research Data Alliance (RDA) FAIR for Research Software (FAIR4RS) Working Group is the most extensive on the topic. Just like the original FAIR guiding principles, their FAIR4RS Principles are aspirational by design and do not provide actionable instructions to the researchers for making their software reusable.
The FAIR-BioRS guidelines were established to fill this gap. They are a set of minimal and actionable step-by-step instructions for biomedical researchers to make their research software compliant with the FAIR4RS principles. The process for developing these guidelines, based on a thorough review of current practices in the field and community inputs, is available in our associated manuscript.